Paper Group NANR 152
Exploring the value space of attributes: Unsupervised bidirectional clustering of adjectives in German. Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement. A Publicly Available Indonesian Corpora for Automatic Abstractive and Extractive Chat Summarization. Dueling Bandits: Beyond Condorcet Winners to Ge …
Exploring the value space of attributes: Unsupervised bidirectional clustering of adjectives in German
| Title | Exploring the value space of attributes: Unsupervised bidirectional clustering of adjectives in German |
| Authors | Wiebke Petersen, Oliver Hellwig |
| Abstract | The paper presents an iterative bidirectional clustering of adjectives and nouns based on a co-occurrence matrix. The clustering method combines a Vector Space Models (VSM) and the results of a Latent Dirichlet Allocation (LDA), whose results are merged in each iterative step. The aim is to derive a clustering of German adjectives that reflects latent semantic classes of adjectives, and that can be used to induce frame-based representations of nouns in a later step. We are able to show that the method induces meaningful groups of adjectives, and that it outperforms a baseline k-means algorithm. |
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| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1267/ |
| https://www.aclweb.org/anthology/C16-1267 | |
| PWC | https://paperswithcode.com/paper/exploring-the-value-space-of-attributes |
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Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement
| Title | Pairwise Word Interaction Modeling with Deep Neural Networks for Semantic Similarity Measurement |
| Authors | Hua He, Jimmy Lin |
| Abstract | |
| Tasks | Answer Selection, Paraphrase Generation, Question Answering, Semantic Similarity, Semantic Textual Similarity |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1108/ |
| https://www.aclweb.org/anthology/N16-1108 | |
| PWC | https://paperswithcode.com/paper/pairwise-word-interaction-modeling-with-deep |
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A Publicly Available Indonesian Corpora for Automatic Abstractive and Extractive Chat Summarization
| Title | A Publicly Available Indonesian Corpora for Automatic Abstractive and Extractive Chat Summarization |
| Authors | Fajri Koto |
| Abstract | In this paper we report our effort to construct the first ever Indonesian corpora for chat summarization. Specifically, we utilized documents of multi-participant chat from a well known online instant messaging application, WhatsApp. We construct the gold standard by asking three native speakers to manually summarize 300 chat sections (152 of them contain images). As result, three reference summaries in extractive and either abstractive form are produced for each chat sections. The corpus is still in its early stage of investigation, yielding exciting possibilities of future works. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1129/ |
| https://www.aclweb.org/anthology/L16-1129 | |
| PWC | https://paperswithcode.com/paper/a-publicly-available-indonesian-corpora-for |
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Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions
| Title | Dueling Bandits: Beyond Condorcet Winners to General Tournament Solutions |
| Authors | Siddartha Y. Ramamohan, Arun Rajkumar, Shivani Agarwal, Shivani Agarwal |
| Abstract | Recent work on deriving $O(\log T)$ anytime regret bounds for stochastic dueling bandit problems has considered mostly Condorcet winners, which do not always exist, and more recently, winners defined by the Copeland set, which do always exist. In this work, we consider a broad notion of winners defined by tournament solutions in social choice theory, which include the Copeland set as a special case but also include several other notions of winners such as the top cycle, uncovered set, and Banks set, and which, like the Copeland set, always exist. We develop a family of UCB-style dueling bandit algorithms for such general tournament solutions, and show $O(\log T)$ anytime regret bounds for them. Experiments confirm the ability of our algorithms to achieve low regret relative to the target winning set of interest. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6337-dueling-bandits-beyond-condorcet-winners-to-general-tournament-solutions |
| http://papers.nips.cc/paper/6337-dueling-bandits-beyond-condorcet-winners-to-general-tournament-solutions.pdf | |
| PWC | https://paperswithcode.com/paper/dueling-bandits-beyond-condorcet-winners-to |
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Modeling Extractive Sentence Intersection via Subtree Entailment
| Title | Modeling Extractive Sentence Intersection via Subtree Entailment |
| Authors | Omer Levy, Ido Dagan, Gabriel Stanovsky, Judith Eckle-Kohler, Iryna Gurevych |
| Abstract | Sentence intersection captures the semantic overlap of two texts, generalizing over paradigms such as textual entailment and semantic text similarity. Despite its modeling power, it has received little attention because it is difficult for non-experts to annotate. We analyze 200 pairs of similar sentences and identify several underlying properties of sentence intersection. We leverage these insights to design an algorithm that decomposes the sentence intersection task into several simpler annotation tasks, facilitating the construction of a high quality dataset via crowdsourcing. We implement this approach and provide an annotated dataset of 1,764 sentence intersections. |
| Tasks | Abstractive Text Summarization, Natural Language Inference |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1272/ |
| https://www.aclweb.org/anthology/C16-1272 | |
| PWC | https://paperswithcode.com/paper/modeling-extractive-sentence-intersection-via |
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Extracting Aspect Specific Opinion Expressions
| Title | Extracting Aspect Specific Opinion Expressions |
| Authors | Abhishek Laddha, Arjun Mukherjee |
| Abstract | |
| Tasks | Aspect-Based Sentiment Analysis, Opinion Mining, Sentiment Analysis |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1060/ |
| https://www.aclweb.org/anthology/D16-1060 | |
| PWC | https://paperswithcode.com/paper/extracting-aspect-specific-opinion |
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Evaluating Machine Translation in a Usage Scenario
| Title | Evaluating Machine Translation in a Usage Scenario |
| Authors | Rosa Gaudio, Aljoscha Burchardt, Ant{'o}nio Branco |
| Abstract | In this document we report on a user-scenario-based evaluation aiming at assessing the performance of machine translation (MT) systems in a real context of use. We describe a sequel of experiments that has been performed to estimate the usefulness of MT and to test if improvements of MT technology lead to better performance in the usage scenario. One goal is to find the best methodology for evaluating the eventual benefit of a machine translation system in an application. The evaluation is based on the QTLeap corpus, a novel multilingual language resource that was collected through a real-life support service via chat. It is composed of naturally occurring utterances produced by users while interacting with a human technician providing answers. The corpus is available in eight different languages: Basque, Bulgarian, Czech, Dutch, English, German, Portuguese and Spanish. |
| Tasks | Machine Translation |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1001/ |
| https://www.aclweb.org/anthology/L16-1001 | |
| PWC | https://paperswithcode.com/paper/evaluating-machine-translation-in-a-usage |
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Search Space Pruning: A Simple Solution for Better Coreference Resolvers
| Title | Search Space Pruning: A Simple Solution for Better Coreference Resolvers |
| Authors | Nafise Sadat Moosavi, Michael Strube |
| Abstract | |
| Tasks | Coreference Resolution |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1115/ |
| https://www.aclweb.org/anthology/N16-1115 | |
| PWC | https://paperswithcode.com/paper/search-space-pruning-a-simple-solution-for |
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Deep Lexical Segmentation and Syntactic Parsing in the Easy-First Dependency Framework
| Title | Deep Lexical Segmentation and Syntactic Parsing in the Easy-First Dependency Framework |
| Authors | Matthieu Constant, Joseph Le Roux, Nadi Tomeh |
| Abstract | |
| Tasks | Dependency Parsing, Lexical Analysis |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1127/ |
| https://www.aclweb.org/anthology/N16-1127 | |
| PWC | https://paperswithcode.com/paper/deep-lexical-segmentation-and-syntactic |
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Patterns of Wisdom: Discourse-Level Style in Multi-Sentence Quotations
| Title | Patterns of Wisdom: Discourse-Level Style in Multi-Sentence Quotations |
| Authors | Kyle Booten, Marti A. Hearst |
| Abstract | |
| Tasks | |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1134/ |
| https://www.aclweb.org/anthology/N16-1134 | |
| PWC | https://paperswithcode.com/paper/patterns-of-wisdom-discourse-level-style-in |
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Right-truncatable Neural Word Embeddings
| Title | Right-truncatable Neural Word Embeddings |
| Authors | Jun Suzuki, Masaaki Nagata |
| Abstract | |
| Tasks | Dependency Parsing, Machine Translation, Part-Of-Speech Tagging, Question Answering, Semantic Role Labeling, Sentiment Analysis, Word Embeddings |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1135/ |
| https://www.aclweb.org/anthology/N16-1135 | |
| PWC | https://paperswithcode.com/paper/right-truncatable-neural-word-embeddings |
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A Character-Aware Encoder for Neural Machine Translation
| Title | A Character-Aware Encoder for Neural Machine Translation |
| Authors | Zhen Yang, Wei Chen, Feng Wang, Bo Xu |
| Abstract | This article proposes a novel character-aware neural machine translation (NMT) model that views the input sequences as sequences of characters rather than words. On the use of row convolution (Amodei et al., 2015), the encoder of the proposed model composes word-level information from the input sequences of characters automatically. Since our model doesn{'}t rely on the boundaries between each word (as the whitespace boundaries in English), it is also applied to languages without explicit word segmentations (like Chinese). Experimental results on Chinese-English translation tasks show that the proposed character-aware NMT model can achieve comparable translation performance with the traditional word based NMT models. Despite the target side is still word based, the proposed model is able to generate much less unknown words. |
| Tasks | Machine Translation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1288/ |
| https://www.aclweb.org/anthology/C16-1288 | |
| PWC | https://paperswithcode.com/paper/a-character-aware-encoder-for-neural-machine |
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CYUT-III System at Chinese Grammatical Error Diagnosis Task
| Title | CYUT-III System at Chinese Grammatical Error Diagnosis Task |
| Authors | Po-Lin Chen, Shih-Hung Wu, Liang-Pu Chen, Ping-Che Yang |
| Abstract | This paper describe the CYUT-III system on grammar error detection in the 2016 NLP-TEA Chinese Grammar Error Detection shared task CGED. In this task a system has to detect four types of errors, in-cluding redundant word error, missing word error, word selection error and word ordering error. Based on the conditional random fields (CRF) model, our system is a linear tagger that can detect the errors in learners{'} essays. Since the system performance depends on the features heavily, in this paper, we are going to report how to integrate the collocation feature into the CRF model. Our system presents the best detection accuracy and Identification accuracy on the TOCFL dataset, which is in traditional Chi-nese. The same system also works well on the simplified Chinese HSK dataset. |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4909/ |
| https://www.aclweb.org/anthology/W16-4909 | |
| PWC | https://paperswithcode.com/paper/cyut-iii-system-at-chinese-grammatical-error |
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Incorporating Side Information into Recurrent Neural Network Language Models
| Title | Incorporating Side Information into Recurrent Neural Network Language Models |
| Authors | Cong Duy Vu Hoang, Trevor Cohn, Gholamreza Haffari |
| Abstract | |
| Tasks | Image Captioning, Language Modelling, Machine Translation, Speech Recognition, Text Generation |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1149/ |
| https://www.aclweb.org/anthology/N16-1149 | |
| PWC | https://paperswithcode.com/paper/incorporating-side-information-into-recurrent |
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$K$-Embeddings: Learning Conceptual Embeddings for Words using Context
| Title | $K$-Embeddings: Learning Conceptual Embeddings for Words using Context |
| Authors | Thuy Vu, D. Stott Parker |
| Abstract | |
| Tasks | Word Embeddings |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1151/ |
| https://www.aclweb.org/anthology/N16-1151 | |
| PWC | https://paperswithcode.com/paper/k-embeddings-learning-conceptual-embeddings |
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